Experimental and modeling study of O and Cl atoms surface recombination reactions in O2 and Cl2 plasmas
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Bibliographic record
Abstract
In low-pressure plasmas commonly used in materials processing, plasma–wall inter-actions play a crucial role in the evolution of the plasma properties both over time and across large-area wafers. We have recently studied the heterogeneous recombination of O and Cl atoms on reactor walls in O 2 and Cl 2 plasmas through both experiments and modeling. The Langmuir–Hinshelwood (i.e., delayed) recombination was investigated using a “spinning-wall” technique in which a portion of the substrate surface is periodically exposed to an inductively coupled plasma and to a differentially pumped chamber where either Auger electron spectroscopy (AES) or line-of-sight mass spectrometry (MS) is used to detect surface and desorbing species. In this paper, a review of the various effects driving the O and Cl atoms recombination dynamics on anodized aluminum (AA) and stainless steel (SS) surfaces is presented. It is shown that recombination probabilities, γ , can vary following plasma exposure due to surface conditioning. In Cl 2 plasmas, γ was also found to depend on the Cl-to-Cl 2 number density ratio, a mechanism ascribed to a competition for adsorption sites between Cl and Cl 2 . We have also determined the recombination rates of Cl atoms in Cl 2 high-density plasmas sustained by electromagnetic surface waves by comparing the measured degrees of dissociation of Cl 2 to those predicted by an isothermal fluid model. For a reactor with large SS and quartz surfaces exposed to the plasma, γ values and their dependence on the Cl-to-Cl 2 number density ratio were consistent with those obtained from the rotating substrate technique. Similar values were obtained for plasmas sustained in a quartz discharge tube. It is expected that for plasmas sustained in or adjacent to a silica tube or plate, the Cl atoms recombination coefficient becomes independent of chamber wall material due to reactor seasoning, producing a silicon-oxychloride layer.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it